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81

Python, the Fundamentals
Einar Smith
Texts in Computational Science and Engineering ISBN: 9783031169717
Texts in Computational Science and Engineering ISBN: 9783030608071

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82

PyHasse Software for Partial Order Analysis: Scientific Background and Description of Selected Modules
Rainer Brüggemann ; Kristina Voigt ; Lars Carlsen ; et al.
Multi-indicator Systems and Modelling in Partial Order ISBN: 9781461482222

13. Climate action
Buch
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83

An introductory guide for conducting psychological research with big data.
Vezzoli, Michela ; Zogmaister, Cristina
Psychol Methods

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84

Automation of the Formation of a Mathematical Formulation of Kinetics for Multistage Chemical Reactions and Numerical Solution to a Direct Problem
N. A. Lysenko ; K. F. Koledina
Advanced Engineering Research, Vol 23, Iss 4, Pp 398-409 (2023)

kinetic analysis mathematical formulation automation differential equation sy... direct problem computational methods
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85

A general biological simulator: the multiscale object oriented simulation environment, MOOSE.
Ray, Subhasis ; Deshpande, Raamesh ; Dudani, Niraj ; et al.
BMC Neuroscience; 2008 Supplement 1, Vol. 9, Special section p1-2, 2p

BIOLOGICAL models SIMULATION methods & mod... OBJECT-oriented methods... COMPUTATIONAL biology C++ PYTHON programming langu...
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86

Multiscale modeling and interoperability in MOOSE.
Dudani, Niraj ; Ray, Subhasis ; George, Siji ; et al.
BMC Neuroscience; 2009 Supplement 1, Vol. 10, Special section p1-2, 2p

SIMULATION methods & mod... MOLECULES BIOLOGICAL neural networ... NEURONS NEURAL conduction PYTHON programming langu...
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87

The ReIMAGINE Multimodal Warehouse: Using Artificial Intelligence for Accurate Risk Stratification of Prostate Cancer.
Santaolalla A ; Hulsen T ; Davis J ; et al.
Publisher: Frontiers Media SA Country of Publication: Switzerland NLM ID: 101770551 Publication Model: eCollection Cited Medium: Internet ISSN: 2624-8212 (Electronic) Linking ISSN: 26248212 NLM ISO Abbreviation: Front Artif Intell Subsets: PubMed not MEDLINE

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88

Developing and Implementing Cloud-Based Tutorials That Combine Bioinformatics Software, Interactive Coding, and Visualization Exercises for Distance Learning on Structural Bioinformatics
Engelberger, Felipe ; Galaz-Davison, Pablo ; Bravo, Graciela ; et al.
7

Biology Information Science Computer Software Tutoring Distance Education Programming
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89

Planning the activities of operational fire departments based on indicators of water consumption for extinguishing fires
Konstantin Sergeevich Vlasov
Technology of technosphere safety. :114-126

13. Climate action 6. Clean water
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91

An automated, unobtrusive, formative assessment of creativity in a computer science and music remixing learning environment.
Rahimi, Seyedahmad ; Smith, Jason Brent ; Truesdell, Erin J. K. ; et al.
Psychol Aesthet Creat Arts

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92

Symmetry, separation, and stability: Physical properties for effective dosimetric space with a stabilized hyaluronic acid spacer.
Svatos, Michelle ; Chell, Erik ; Low, Daniel A. ; et al.
Medical Physics. Sep2024, Vol. 51 Issue 9, p6231-6245. 15p.

MEDICAL dosimetry PYTHON programming langu... SYMMETRY groups HYALURONIC acid POLYETHYLENE glycol PROSTATE
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94

Programski paket Astropy
Pranjić, Ivan ; Bilalbegović, Goranka ; Jerbić-Zorc, Gorjana ; et al.

programming language Pyt... programski jezik Python PRIRODNE ZNANOSTI. Fizik... Astroquery Programski jezik Python Astropy
Dissertation
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95

pyCTQW: A continuous-time quantum walk simulator on distributed memory computers.
Izaac, Josh A. ; Wang, Jingbo B.
Computer Physics Communications. Jan2015, Vol. 186, p81-92. 12p.

COMPUTER storage devices CONTINUOUS time systems QUANTUM information theo... ALGORITHMS COMPUTER software
Zeitschrift
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96

Earth-Mars trajectories with lunar gravity assist study using the self-adaptive Levenberg-Marquardt Algorithm
Rosa, Flávio Daniel Dias ; Bousson, Kouamana ; uBibliorum
urn:tid:202547248

Assistência Gravitaciona... Marte Self-Adaptive Levenberg-... Transferência Interplane...
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97

A general-purpose framework for genetic improvement
Marino, Francesco ; Squillero, Giovanni ; Tonda, Alberto ; et al.
14. International Conference PPSN, Sep 2016, Edimbourg, United Kingdom. ⟨10.1007/978-3-319-45823-6_32⟩

Edimbourg, United Kingdo... Genetic improvement Genetic programming Linear genetic programmi... Software engineering [SDV]Life Sciences [q-bi...
Konferenz
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98

Computación Evolutiva Descentralizada de Modelo Híbrido usando Blockchain y Prueba de Trabajo de Optimización
Consultor de tesis ; Pabón Burbano, María Constanza ; Bastidas Caicedo, Harvey Demian ; et al.
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Lienig, "A parallel genetic algorithm for performance-driven VLSI routing," IEEE Trans. Evol. Comput, vol. 1, no. 1, pp. 29-39, 1997.; H. Piereval, "Distributed evolutionary algorithms for simulation optimization," IEEE Trans Sys. Man. Cybern. , vol. 30, no. 1, pp. 15-24, 2000.; K.C.Tan, "Automating the drug-sheduling of cancer chemotherapy via evolutionary computation," Artif.Intellig.Med., vol. 25, no. 2, pp. 169-185, 2002.; J. Creput, "Automatic mesh generation for mobile network dimensioning using evolutionary approach," Evol.Comput, vol. 9, no. 1, pp. 18-30, 2005.; J.Liu, "An evolutionary autonomous agents approach to image feature extraction.," IEEE Trans. Evol. Comput., vol. 1, no. 2, pp. 141-158, 1997.; M. Epitropakis, "Hardware-friendly higher-order neural network training using distributed evolutionary algorithms.," Appl. Soft. comput. , vol. 10, no. 2, pp. 398-408, 2010.; L. Kattan, "Distributed evolutionary estimation of of dynamic traffic origin/destination," in 13th IEEE Conference on Intelligent Transport Systems, 2010.; J. Noyima, "Ensemble classifier design by parallel implementation of genetic fuzzy rule selection for large datasets.," in IEEE Congress on Evolutionary Computation, 2010.; F. Rainville, "DEAP: A Python Framework for Evolutionary Algorithms," in GECCO, 2012.; M. Linder, "Grid computing in Matlab for solving evolutionary algorithms," in Technical Computing Bratislava, Bratislava, 2012.; J. Kennedy and R. Eberhart, "Particle Swarm Optimization," in Proceedings of IEEE International Conference on Neural Networks. , 1995.; D. D. Karaboga, "An Idea Based On Honey Bee Swarm for Numerical Optimization," Erciyes University, 2005.; M. Dorigo, "Distributed Optimization by Ant Colonies," in Première conférence européenne sur la vie artificielle, Paris, France, 1991.; C. Huang, "A hybrid stock selection model using genetic algorithms and support vector regression," Applied Soft Computing, vol. 12, p. 807–81, 2012.; E. Levy, "Genetic algorithms and deep learning for automatic painter classification," in conference on Genetic and evolutionary computation - GECCO ’14 , New York, New York, USA, 2014.; E. Levy, "Genetic algorithms and deep learning for automatic painter classification," in Proceedings of the 2014 conference on Genetic and evolutionary computation - GECCO ’14 , New York, New York, USA, 2014.; S. Whiteson, "Evolutionary Function Approximation for Reinforcement Learning," Journal of Machine Learning Research, vol. 8, pp. 877-917, 2006.; R. B. Greve, "Evolving Neural Turing Machines for Reward-based Learning," in Genetic and Evolutionary Computation Conference (GECCO), Denver, Colorado, USA, 2016.; A. Santoro, "One-shot Learning with Memory-Augmented Neural Networks," Cornell University , Ithaca, NY, USA, 2016.; D. Izzo, "The generalized isalnd model," Studies in Computational Intelligence, vol. 415, pp. 151-169, 2012.; G. Folino, "P-CAGE: An Environment for Evolutionary Computation in Peer-to-Peer Systems," in European Conference on Genetic Programming, Berlin, 2006.; A. L. Ian Scriven, "Decentralised distributed multiple objective particle swarm optimisation using peer to peer networks," in IEEE World Congress on Evolutionary Computation, 2008. CEC 2008, 2008.; A. L. C. Fernando Silva, "odNEAT: An Algorithm for Decentralised Online Evolution of Robotic Controllers," Evolutionary Computation , vol. 23, no. 3, pp. 421-449, 2015.; D. Jakobović, "ECF - Evolutionary Computation Framework," University of Zagreb,; M. A. García-Sánchez P., "A Methodology to Develop Service Oriented Evolutionary Algorithms," Intelligent Distributed Computing VIII, vol. 570, 2015.; S. Cahon, "ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics," Journal of Heuristics, vol. 10, no. 3, pp. 357-380, 2004.; D. R. White, "Software review: the ECJ toolkit," Genetic Programming and Evolvable Machines, vol. 13, no. 1, pp. 65-67, 2011.; M. G. Arenas, "A Framework for Distributed Evolutionary Algorithms," Lecture Notes on Computer Science, vol. 2439, pp. 665-675, 2002.; J. L. J. Laredo, "Resilience to churn of a peer-to-peer evolutionary algorithm," International Journal of High Performance Systems Architecture, vol. 1, no. 4, pp. 260-268, 2008.; C. Rohrs, "Query Routing for the Gnutella Network," Lime Wire LLC, 2002.; R. Fielding, "Chapter 5: Representational State Transfer (REST)," in Architectural Styles and the Design of Network-based Software Architectures, Irvine, Ca, University of California, 2000.; P. C. R. K. Len Bass, Software Architecture in Practice - Second Edition, Addison Wesley, 2003.; S. 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Moody, "Learning to trade via direct reinforcement," IEEE Transactions on Neural Networks, vol. 12, no. 4,, 2001; C. WATKINS, "Q,-Learning," Machine Learning, vol. 8, 1992.; R. M. Kenneth O. Stanley, "Efficient Reinforcement Learning through Evolving Neural Network Topologies," in Genetic and Evolutionary Computation Conference , San Francisco, CA, 2002.; C. Igel, "Neuroevolution for reinforcement learning using evolution strategies," in Congress on Evolutionary Computation, 2003.; V. Heidrich-Meisner, "Neuroevolution strategies for episodic reinforcement learning," Journal of Algorithms, vol. 64, no. 4, pp. 152-168, 2009.; D. Lessin, "Open-ended behavioral complexity for evolved virtual creatures," in 15th annual conference on Genetic and evolutionary computation, Amsterdam, The Netherlands, 2013.; G. B. a. V. Cheung, "OpenAI Gym," Arxiv, vol. arXiv:1606.01540, 2016.; N. G. L. Iker Zamora, "Extending the OpenAI Gym for robotics: a toolkit for reinforcement learning using ROS and Gazebo," Whitepaper, 2016.; A. H. David Silver, "Mastering the game of Go with deep neural networks and tree 62 search," Nature, vol. 529, no. 7587, pp. 484-489, 2016.; K. K. Volodymyr Mnih, "Human-level control through deep reinforcement learning," Nature, vol. 518, no. 7540, pp. 529-533, 2015.; U. B. o. E. Analysis, "U.S. INTERNATIONAL TRADE IN GOODS AND SERVICES - December 2013," U.S. Department of Commerce, Washington, DC 20230, 2013.; E. Department, "Triennial Central Bank Survey of foreign exchange and OTC derivatives markets in 2016," Bank For International Settlements, Basel, Switzerland,; Investopedia, "Forex Broker Definition,"; Investopedia, "Margin Call Definition,"; Investopedia, "What is a Spread,"; Investopedia, "Leverage Definition,"; A. P. CHABOUD, "Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market," Journal of the American Finance Association, vol. 69, no. 5, p. 2045–2084 , 201.; M. A. H. Dempster, "An automated FX trading system using adaptive reinforcement learning," Expert Systems with Applications, vol. 30, no. 3, pp. 543-552, 2006.; HistData.com, "Free Forex Historical Data Repository,"; R. T. Fielding, "Chapter 5: Representational State Transfer (REST)," in Architectural Styles and the Design of Network-based Software Architectures, Irvine, University of California, 2000.; H. W. Group, " SOAP: Simple Object Access Protocol," [Online]. Available:; e. a. Don Box, "Simple Object Access Protocol (SOAP) 1.1," W3C, 8 May 2000. [Online]. Available:; J.-R. W. Group, "JSON-RPC 2.0 Specification," JSON-RPC Working Group, 04 01 2013. [Online]. Available:; R. Mikkulainen and J. e. a. Liang, "Evolving Deep Neural Netwokrs," eprint arXiv:1703.00548, 2017.; Reponame:Vitela: Repositorio Institucional PUJ; Instname:Pontificia Universidad Javeriana Cali

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99

Digital typography in the new millennium: Flexible documents by a flexible engine
Loverdos, C.K.K. Syropoulos, A. ; Loverdos, C.K.K. Syropoulos, A.

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100

A formal analysis of the standard operating processes (SOP) and multiple time scales (MTS) theories of habituation.
Jorquera, Orlando E. ; Farfán, Osvaldo M. ; Galarce, Sergio N. ; et al.
Psychol Rev

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